{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.fftpack import fft,ifft\n",
    "import pandas as pd\n",
    "from scipy.optimize import minimize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data11 = pd.read_csv(\"energy_2011.csv\")  \n",
    "x11 = data11['x']\n",
    "y11 = data11['y']\n",
    "xerr11 = data11['xerr']\n",
    "yerr11 = data11['yerr']\n",
    "\n",
    "data142 = pd.read_csv(\"energy_2014_2.csv\")  \n",
    "x142 = data142['x']\n",
    "y142 = data142['y']\n",
    "xerr142 = data142['xerr']\n",
    "yerr142 = data142['yerr']\n",
    "\n",
    "data15 = pd.read_csv(\"energy_2015.csv\")  \n",
    "x15 = data15['x']\n",
    "y15 = data15['y']\n",
    "xerr15 = data15['xerr']\n",
    "yerr15 = data15['yerr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,8))\n",
    "plt.loglog()\n",
    "plt.errorbar(x11, y11, yerr=yerr11, xerr=xerr11, fmt='.', label='2011')\n",
    "plt.errorbar(x142, y142, yerr=yerr142, xerr=xerr142, fmt='.', label='2014(2)')\n",
    "plt.errorbar(x15, y15, yerr=yerr15, xerr=xerr15, fmt='.', label='2015')\n",
    "plt.xlabel(\"Energy (keV)\",fontsize=15)\n",
    "plt.ylabel(r\"$keV^2 (Photons{\\ }cm^{-2}{\\ } s^{-1}{\\ } keV^{-1})$\",fontsize=15)\n",
    "plt.legend(fontsize=13)\n",
    "plt.tick_params(labelsize=13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
